WO2023274508A1

WO2023274508A1 - Conflict detection of specific intents in an intent-based network

Info

Publication number: WO2023274508A1
Application number: PCT/EP2021/067822
Authority: WO
Inventors: Péter SZILÁGYI; Csaba VULKÁN
Original assignee: Nokia Technologies Oy
Priority date: 2021-06-29
Filing date: 2021-06-29
Publication date: 2023-01-05

Abstract

For each specific intent received by an intent management entity of an intent-based network, one or more targets to be managed by a quality management entity of the intent-based network are calculated (S101). Resource pool information is collected from control entities and network functions which control resource pools comprising resources allocated to end user services (S103), and feedback on quality is collected from terminating entities terminating the end user services (S105). Based on at least one of the resource pool information and the feedback on quality, it is evaluated whether or not the one or more targets are achievable (S107).

Description

CONFLICT DETECTION OF SPECI FI C I NTENTS I N AN I NTENT- BASED

NETWORK

TECHNI CAL FI ELD

At least some example embodiments relate to conflict detection of specific intents, e.g., quality of experience (QoE) intents, in an intent-based network.

BACKGROUND

An intent-based network is a network that is capable of interpreting intents and is equipped with the intelligence to take steps towards fulfilling/assuring them .

LI ST OF ABBREVIATIONS

3GPP 3rd Generation Partnership Project

AF Application Function

API Application Programm ing I nterface

CPU Central Processing Unit

DC Domain Controller

DRB Data Radio Bearer

HTTP HyperText Transfer Protocol

I D Identifier

I M I ntent Manager

NEF Network Exposure Function

NF Network Function

O-RAN Open RAN

OTT Over The Top

PRB Physical Resource Block

QM QoE Manager

QoE Quality of Experience

QoS Quality of Service

RAN Radio Access Network

RC Resource Controller RI C Radio I ntelligent Controller

RRC Radio Resource Control

RT Real Tim e

UE User Equipment

ZSM Zero-touch Service and network Management

SUMMARY

Specific intents are intents which indicate that a certain subject has to have a certain quality. An example of such specific intents are QoE intents which declare that an end user experience of a certain end user service should be satisfactory. Ensuring good QoE for end user services is technically a resource m anagem ent problem , which has to be solved by the intent-based network autom atically. QoE driven resource m anagem ent requires the intent-based network to dynam ically allocate sufficient amount of resources to each end user service from every resource pool, e.g. , RAN PRB, link capacity, virtual CPU, etc. , that is used for providing the service. For a given service, the sam e amount of resources (e.g., RAN PRB) may allow different levels of QoE depending on dynam ic UE and network conditions (e.g. , UE radio channel quality) , which define the resource dem and of the service (i.e., the am ount of resources needed for the service to have good QoE) . Assuring/fulfilling m ultiple QoE intents sim ultaneously requires that com mon resources are scheduled so that each end user service is allocated at least as m uch resources from the com m on resource pool as its resource dem and. As the resource demand may vary according to the network conditions, as well as due to end user, application or content level dynam ics, the intent-based network needs to dynam ically change the services' resource allocation or arbitrate the scheduling schem e that defines how com m on resources are split among m ultiple services. If such scheduling is exercised over a com m on resource pool, good QoE is achieved for all services who consum e resources from the pool.

There are m ultiple reasons why such scheduling m ay not be possible: (1 ) the resource pool's capacity is lower than the cumulative resource demand of the services using it;

(2) the resource scheduler's capabilities are insufficient to split the resources in the right way, e.g., it has an allocation granularity that prevents the allocation of arbitrarily small amount of resources, or it can only operate according to a finite number of allocation presets that prevents stepping in between adjacent configurations. Both types of problems may prevent the assurance/fulfillment of QoE intents, but for different reason, thus calling for potentially different corrective actions.

At least some example embodiments aim at solving the above problems.

According to at least some example embodiments, a method, an apparatus and a non-transitory computer-readable storage medium are provided as specified by the appended claims.

According to at least some example embodiments, an intent-based network is enabled to detect the type of resource allocation problems in the context of specific intents such as QoE intents and report it to enable resolution of the problems.

In the following example embodiments and example implementations will be described with reference to the accompanying drawings.

BRI EF DESCRI PTI ON OF THE DRAW I NGS

Fig. 1 shows a flowchart illustrating a process of conflict detection of specific intents according to at least some example embodiments.

Fig. 2 shows a schematic diagram illustrating a configuration and interfaces of a conflict detection apparatus comprising an intent management entity and a quality management entity according to at least some example embodiments. Fig. 3 shows a flowchart illustrating a process for conflict detection performed by the intent management entity according to at least some example embodiments.

Fig. 4 shows a flowchart illustrating a process for conflict detection performed by the quality management entity according to at least some example embodiments.

Fig. 5 shows a schematic diagram illustrating resource pool information according to at least some example embodiments.

Fig. 6 shows a schematic diagram illustrating service to resource pool mapping according to at least some example embodiments.

Fig. 7 shows a schematic diagram illustrating an example implementation of the conflict detection apparatus of Fig. 2 in an O-RAN architecture.

Fig. 8 shows a schematic block diagram illustrating a configuration of control units in which example embodiments are implementable.

DESCRIPTION OF THE EMBODIMENTS

Fig. 1 shows a flowchart illustrating a process of conflict detection of specific intents in an intent-based network according to at least some example embodiments.

A specific intent as used herein indicates that a certain subject has to have a certain quality. The certain subject is associated with an end user service. An example of the specific intent is a QoE intent.

For each specific intent of a plurality of specific intents received by an intent management entity of the intent-based network, one or more targets to be managed by a quality management entity of the intent-based network are calculated (S101 ). The one or more targets indicate management subjects associated with the certain subject and with the end user service.

The management entity collects resource pool information from control entities and network functions which control resource pools comprising resources allocated to end user services, wherein the management subjects of the plurality of specific intents are associated with the end user services (S103).

The management entity also collects feedback on quality from terminating entities terminating the end user services (S105).

Based on at least one of the resource pool information and the feedback on quality, it is evaluated whether or not the one or more targets of the plurality of specific intents are achievable (S107).

According to at least some example embodiments, the quality management entity maintains a mapping of each of the end user services to one or more of the resource pools based on the resource pool information.

According to at least some example embodiments, in S107, the quality management entity decides that the one or more targets are not achievable in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is lower than a sum of a per service resource demand for services using resources from the resource pool, and indicates, to the intent management entity, an enforcement conflict due to capacity of the resource pool.

According to at least some example embodiments, in S107, in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is not lower than a sum of a per service resource demand for services using resources from the resource pool, the quality management entity reconfigures the control entities and network functions to control split of the resource pool among the services and align a per service resource allocation with the per service resource demand.

According to at least some example embodiments, in case the per service resource allocation cannot be aligned with the per service resource demand, the quality management entity decides that the one or more targets are not achievable, and indicates, to the intent management entity, an enforcement conflict due to allocation granularity.

According to at least some example embodiments, a method and apparatus for an intent based network that enable the detection of different types of QoE enforcement conflicts during the assurance/fulfillment of multiple QoE Intents are proposed.

Fig. 2 shows a schematic diagram illustrating a configuration and interfaces of a conflict detection apparatus comprising an intent management entity and a quality management entity according to at least some example embodiments.

As shown in Fig. 2, the apparatus comprises an intent management entity, e.g. an Intent Manager (IM) 210, and a quality management entity, e.g. a QoE Manager (QM) 220, which together perform the process of Fig. 1 to fulfill/assure QoE Intents received from an operator and to detect QoE enforcement conflicts if the QoE Intents cannot be fulfilled/assured simultaneously. An aspect of the process is transforming QoE Intent fulfillment/assurance objectives into a closed-loop QoE driven resource management automation task. In the following, functions of the intent management entity in the process of Fig. 1 will be described in more detail by referring to Figs. 2 and 3, where the IM 210 is an example of the intent management entity.

The IM 210 receives QoE intents from the operator. For each QoE Intent, the I M 210 provides one or more QoE targets for the QM 220 ( S 101 ) , which will be described in more detail below. The QM 220 supervises a set of Domain Controllers (DC), Resoure Controllers (RC) and/or Network Functions (NF) 230 by using their North-bound APIs to influence resource allocation decisions and thereby enforce the QoE targets for the end user services, which will be described in more detail below. The QM 220 obtains resource allocation information from the DC/RC/NFs 230 (S103) and QoE feedback from a UE/AF/ Application Server 240 terminating the end user services (S105). These inputs are used by the QM 220 to evaluate (S107) whether the resource pools controlled by the DC/RC/NFs 230 have sufficient capacity to ensure the QoE of the services, and if yes, whether they are able to enforce the right resource split among the services competing for the same resources, which will be described in more detail below.

The QoE Intents, received by the IM 210 from the operator, declare that the QoE of a certain end user service or application should be satisfactory (e.g. that the certain end user service or application has to have a certain quality). As illustrated in Fig. 3, in S301 , the IM 210 receives a QoE Intent from the operator, the QoE Intent declaring a subject of the QoE intent. According to at least some example embodiments, the subject comprises at least one of a group of users, an application type, a subset of a service or a service.

Optionally, the QoE Intent further declares conditions of the QoE intent, e.g., the QoE intent contains one or more constraints on measurable parameters, such as: traffic metrics (up to which the QoE should be enforced, such as a maximum throughput value); time (such as daily time window when the intent should be active); area (geographical area or set of NFs such as RAN entities); user/subscriber category or individual; etc.

Optionally, the QoE Intent also contains a priority value to indicate the relative importance of QoE Intents.

In S302, the IM 210 translates each QoE Intent to one or more QoE targets. Each QoE target describes an exact subject of the QoE management, e.g., one or more of a specific user, a specific application, a specific subset of a service or a specific service, etc.

According to at least some example embodiments, optionally, the QoE targets describe resource limits up to which the QoE should be enforced.

According to at least some example embodiments, optionally, the QoE targets describe a priority among the QoE targets to indicate to the QM 220 which target is more important.

According to at least some example embodiments, the resource limit and the priority are derived or carried over from the QoE Intent if it contains constraints or a priority value.

In S303, the IM 210 sends the QoE targets to the QM 220.

The QM 220 collects resource pool information from the DC/RC/NFs (S103). The resource pool information describes (1 ) what resource pools are controlled by the DC/RC/NF 230; and (2) what is the amount of resources allocated to each end user service and what is the resource pool's capacity (total amount of resources). According to at least some example embodiments, a resource represents any measure that is quantifiable, has a finite capacity and is allocated by the DC/RC/NF 230. For example, the resources are RAN PRBs in a cell allocated by the cell's radio scheduler. According to at least some example embodiments, the QoE feedback collected by the QM 220 from the UE/AF/ Application Server 240 (S105) is in the form of a QoE Incident, which is an event sent by the source if it momentarily experiences QoE degradation. The QoE Incident abstracts away the specific nature of the end user service and what constitutes as a QoE degradation (e.g., whether the service requires a certain throughput or delay to enjoy good QoE and how much or how long violation of such requirements causes degradation). The uniform QoE Incident event enables the QM 220 to handle any end user service including future ones, making the solution scalable and forward compatible also for future services and applications.

In the following, functions of the quality management entity in the process of Fig. 1 will be described in more detail by referring to Figs. 4 to 6, where the QM 220 is an example of the intent management entity.

As illustrated in Fig. 4, according to at least some example embodiments, based on the resource pool information received from the DC/RC/NFs 230, the QM 220 maintains a mapping between each service and the resource pools (S401 ), where mapping means that the service uses resources from the pool. As a next step, executed for each resource pool, the QM 220 calculates the resource demand of each end user service that is mapped to the resource pool (S403). The resource demand of a service is the amount of resources needed for the service from the resource pool to enable good QoE. The resource demand is used by the QM 220 to check if the resource pool may be a bottleneck limiting the QoE of one or more services, which happens (S407) if there is a QoE incident for at least one service (S403, S404 "Yes") and at the same time the sum of all resource demands is higher than the resource pool's capacity (S405, S406 "Yes"). In this case QoE conflict is declared due to insufficient amount of resources.

Additionally, according to at least some example embodiments, a different type of QoE conflict is detected if the sum of all resource demands is not higher than the resource pool's capacity (S405, S406 "No") but at least one service has QoE incident (S403, S404 "Yes") and that service's resource demand cannot be fulfilled due to limitations in the DC/RC/NF's resource allocation capabilities. If no QoE conflict is present, yet the resource demand of at least one service is not fulfilled by the actual resource allocation, the QM 220 reconfigures the DC/RC/NF 230 to arbitrate the split of the resource pool among the services and align the per service resource allocation with the service's resource demand (S408, S409 "Yes", S411 ).

Steps S402 to S411 are executed for each resource pool of each DC/RC/NF 230. In case there is no QoE incident for at least one service which has been allocated resources from the resource pool currently considered (S404 "No"), the process advances to S411 indicating that a QoE conflict is not present.

In case there is a QoE incident for at least one service which has been allocated resources from the resource pool currently considered (S404 "Yes"), the process advances to S405 in which the sum of the resource demands of the services which have been allocated resources from the resource pool currently considered is compared with the capacity of the resource pool currently considered. In case this sum is higher than the capacity of the resource pool (S406 "Yes"), the process advances to S407 indicating a QoE enforcement conflict due to capacity of the resource pool (not enough resources).

In case the sum of the resource demands is not higher than the capacity of the resource pool (S406 "No"), the process advances to S408 in which it is checked whether a DC/RC/NF configuration exists in which the resource pool is divided among the services so that each service's demand is satisfied. In case such configuration exists (S409 "Yes"), the process advances to S411 indicating that a QoE conflict is not present. Further, in S411 the DC/RC/NF configuration is updated. In case such configuration dos not exist (S409 "No"), the process advances to S410 indicating a QoE enforcement conflict due to allocation granularity (allocation granularity issue).

According to at least some example embodiments, the QM 220 periodically collects resource pool information from each DC/RC/NF 230 it controls. As shown in Fig. 5, according to at least some example embodiments, the resource pool information comprises an indication of the resource pool capacity (total amount of resources) and the current resource use of each service from the resource pool. The resource pool information has two uses: (1 ) map the services to resource pools; (2) help the QM 220 estimate the resource demand of the services, as will be described in more detail below.

For (1 ), mapping the services to resource pools, the QM 220 maintains a mapping hierarchy as shown in Fig. 6. The mapping enables to trace which DC/RC/NF 601 , 602 controls which resource pool 611 to 614, and for each resource pool 611 to 614, which services 621 to 628 are using it. It is noted that a service can use multiple resource pools simultaneously.

For (2), calculating the resource demand of the services, according to at least some example embodiments, the QM 220 considers that in case a service declares a QoE Incident, the current amount of resources it uses is insufficient (demand exceeds usage) and if the service is not declaring QoE Incident, the current amount of resources it uses is sufficient (usage exceeds or equal to demand). According to at least some example embodiments, the current amount of resources used by a service is calculated as a rolling average over a time window rather than using the latest reported data point. According to at least some example embodiments, the QM 220 keeps an estimated resource demand for each service by tracking the service's QoE Incidents in correlation with its current resource usage: the resource usage where QoE Incidents appear yields a lower limit for the services resource demand, whereas the resource usage where QoE Incidents disappear is an upper limit for the same. According to at least some example embodiments, the QM 220 uses an additional clue which is whether there is available (unsued) capacity in the resource pool: available but unused resource means that the resource is not a bottleneck of the QoE as services could use more resources if they needed more. This however is only a valid assumption if the resource allocation mechanism is work conserving and there are no service level limits that prevent a service to grow its usage above a certain threshold. According to at least some example embodiments, such knowledge of a DC/RC/NFs resource allocation strategy and configuration is part of the QM's implementation (statically or obtained dynamically at runtime when connecting to the North-bound APIs of the DC/RC/NF 230) for controlling the DC/RC/NF 230.

In the following, an example implementation of the apparatus of Fig. 2 will be described with reference to Fig. 7.

Fig. 7 illustrates an example implementation of the apparatus of Fig. 2 in the O-RAN architecture with Non-RT RIC 710 and Near-RT RIC 720 having A1 and E2 interfaces. According to at least some example embodiments, the IM 210 is an rApp 711 running on the Non-RT RIC 710 and the QM 220 is an xApp 721 running on the Near-RT RIC 720. The IM 711 interfaces with the operator and receives QoE Intents which are targeting groups of users (e.g., gold subscribers), application types (e.g., video) or services (e.g., OTT/lnternet or native services). The IM 711 translates these QoE Intents to QoE targets, such as a QoE target for a specific user (e.g., identified by UE ID) or a specific application (e.g., YouTube) or both (a specific user's specific application). According to at least some example embodiments, the I M 711 performs steps S101 of Fig. 1 and S301 -S303 of Fig. 3. The QoE targets are provided to the QM 721 on the Non-RT RIC 720 as A1 policies through the A1 interface.

According to at least some example embodiments, the QM 721 performs steps S103, S105, S107 of Fig. 1 and steps S401 -S411 of Fig. 4, and maintains the data structures shown in Figs. 5 and 6. The QM 721 in the Near-RT RIC 720 collects QoE Incidents from a UE/user application 741 and/or from an external AF/ Application Server 742. In the context of O- RAN, QoE Incidents are called enrichment information, however, according to at least some example embodiments, the enrichment information enters the Near-RT RIC 720 as opposed (or in addition) to the current O-RAN enrichment specification where it is collected by the Non-RT RIC. The QM 721 interfaces with a RAN (gNB) 730 to collect resource pool information (e.g., Radio PRB allocation) and to provide configuration (e.g., RAN DRB QoS profile). An O-RAN specific technical problem related to the collection of QoE Incidents is the identification of the UE to which the QoE Incident relates. The RAN 730, UE 741 and Near-RT RIC 720 are all aware of the UE's RAN ID (i.e., the UE's unique identifier within the RAN). However, by default the AF and the Application Server 742 both lack this information.

For solving this problem, according to at least some example embodiments, the UE 741 sends the UE RAN ID to the AF/ Application Server 742 counterpart, and the AF/ Application Server 742 includes this information element in the QoE Incident that it sends to the QM 721 .

Alternatively, according to at least some example embodiments, the UE 741 itself transfers the QoE Incident to the RAN 730 via RRC and the RAN 730 relays it along with the UE RAN ID to the QM 721 via E2.

Now reference is made to Fig. 8 illustrating a simplified block diagram of control unit 810 and 820 that are suitable for use in practicing at least some example embodiments. According to an example implementation, the step S101 of Fig. 1 and steps S301 -303 are implemented by the control unit 810, and steps S103, S105 and S107 of Fig. 1 and steps S401 -411 of Fig. 4 are implemented by the control unit 820.

The control unit 810 comprises processing resources (e.g. processing circuitry) 811 , memory resources (e.g. memory circuitry) 812 and interfaces (e.g. interface circuitry) 813, which are coupled via a wired or wireless connection 814.

Similarly, the control unit 820 comprises processing resources (e.g. processing circuitry) 821 , memory resources (e.g. memory circuitry) 822 and interfaces (e.g. interface circuitry) 823, which are coupled via a wired or wireless connection 824.

According to at least some example implementations, the interfaces 813 comprise interfaces 831 for communicating with an operator, and interfaces 832 for communicating with the control unit 820, e.g. A1 interfaces.

According to at least some example implementations, the interfaces 823 comprise interfaces 832 for communicating with the control unit 810, e.g.

A1 interfaces, and interfaces 833 for communicating with control entities and network functions, e.g. E2 interfaces.

According to an example implementation, the memory resources 812, 822 are of any type suitable to the local technical environment and are implemented using any suitable data storage technology, such as semiconductor based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The processing resources 811 , 821 are of any type suitable to the local technical environment, and include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on a multi core processor architecture, as non-limiting examples.

According to an example implementation, the memory resources 812, 822 comprise one or more non-transitory computer-readable storage media which store one or more programs that when executed by the processing resources 811 , 821 cause the control unit 810, 820 to function as an intent managing entity, quality management entity as described above. Further, as used in this application, the term "circuitry" refers to one or more or all of the following:

(a) hardware-only circuit implementations (such as implementations in only analog and/or digital circuitry) and

(b) to combinations of circuits and software (and/or firmware), such as (as applicable): (i) to a combination of processor(s) or (ii) to portions of processor(s)/software (including digital signal processor(s)) , software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions) and

(c) to circuits, such as a microprocessor(s) or a portion of a microprocessor(s), that require software or firmware for operation, even if the software or firmware is not physically present.

This definition of "circuitry" applies to all uses of this term in this application, including in any claims. As a further example, as used in this application, the term "circuitry" would also cover an implementation of merely a processor (or multiple processors) or portion of a processor and its (or their) accompanying software and/or firmware. The term "circuitry" would also cover, for example and if applicable to the particular claim element, a baseband integrated circuit or applications processor integrated circuit for a mobile phone or a similar integrated circuit in server, a cellular network device, or other network device.

According to at least some example embodiments, an apparatus for use by an intent-based network is provided. The apparatus comprises: for each specific intent of a plurality of specific intents received by an intent management entity of the intent-based network, means for calculating one or more targets to be managed by a quality management entity of the intent-based network, wherein the specific intent indicates that a certain subject has to have a certain quality, wherein the certain subject is associated with an end user service, and wherein the one or more targets indicate management subjects associated with the certain subject and with the end user service; means for collecting resource pool information from control entities and network functions which control resource pools comprising resources allocated to end user services, wherein the management subjects of the plurality of specific intents are associated with the end user services; means for collecting feedback on quality from terminating entities terminating the end user services; and means for evaluating, based on at least one of the resource pool information and the feedback on quality, whether or not the one or more targets of the plurality of specific intents are achievable.

According to at least some example embodiments, the specific intent further indicates at least one of conditions and a priority of the specific intent; and/or the one or more targets further indicate at least one of resource limits and a priority of the management subjects.

According to at least some example embodiments, at least one of the resource limits and the priority of the management subjects are derived from at least one of the conditions and the priority of the specific intent.

According to at least some example embodiments, the evaluating is further based on at least one of the resource limits and a priority of the one or more targets.

According to at least some example embodiments, the resource pool information describes: a total amount of resources of each of the resource pools which are controlled by the control entities and network functions, and for each resource pool of the resource pools, a per service resource demand for services using resources from the resource pool, and wherein the evaluating is performed for each of the resource pools.

According to at least some example embodiments, the feedback on quality comprises an event sent by a terminating entity of the terminating entities in case it momentarily experiences a degradation of the certain quality.

According to at least some example embodiments, the apparatus further comprises: means for maintaining a mapping of each of the end user services to one or more of the resource pools based on the resource pool information.

According to at least some example embodiments, the apparatus further comprises: means for deciding that the one or more targets are not achievable in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is lower than a sum of a per service resource demand for services using resources from the resource pool; and means for indicating, to the intent management entity, an enforcement conflict due to capacity of the resource pool.

According to at least some example embodiments, the apparatus further comprises: means for, in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is not lower than a sum of a per service resource demand for services using resources from the resource pool, reconfiguring the control entities and network functions to control split of the resource pool among the services and align a per service resource allocation with the per service resource demand.

According to at least some example embodiments, the apparatus further comprises: means for, in case the per service resource allocation cannot be aligned with the per service resource demand, deciding that the one or more targets are not achievable; and means for indicating, to the intent management entity, an enforcement conflict due to allocation granularity.

According to at least some example embodiments, at least one of the following applies: the intent management entity comprises a non-real time radio intelligent controller, the quality management entity comprises a near-real time radio intelligent controller, the specific intents comprise quality of experience intents, the specific intents are targeting at least one of groups of users, application types, subsets of services or services, the certain subject comprises at least one of a group of users, an application type, a subset of a service or a service, the one or more targets comprise at least one of a target for a specific user, a target for a specific application, a target for a specific subset of a service or a target for a specific service, the management subjects comprise at least one of a specific user, a specific application, a specific subset of a service or a specific service, the terminating entities comprise at least one of a user equipment, an application function and an application server, the one or more targets are provided to the quality management entity as A1 policies through A1 interface, the certain quality comprises a satisfactory quality of experience of the certain subject.

According to at least some example embodiments, the feedback on quality includes an identifier of the terminating entities.

According to at least some example embodiments, the feedback on quality from the terminating entities is collected via the control entities and network functions.

It is to be understood that the above description is illustrative and is not to be construed as limiting. Various modifications and applications may occur to those skilled in the art without departing from the true spirit and scope as defined by the appended claims.

Claims

1. A method for use by an intent-based network, the method comprising: for each specific intent of a plurality of specific intents received by an intent management entity of the intent-based network, calculating one or more targets to be managed by a quality management entity of the intent- based network, wherein the specific intent indicates that a certain subject has to have a certain quality, wherein the certain subject is associated with an end user service, and wherein the one or more targets indicate management subjects associated with the certain subject and with the end user service; collecting resource pool information from control entities and network functions which control resource pools comprising resources allocated to end user services, wherein the management subjects of the plurality of specific intents are associated with the end user services; collecting feedback on quality from terminating entities terminating the end user services; and evaluating, based on at least one of the resource pool information and the feedback on quality, whether or not the one or more targets of the plurality of specific intents are achievable.

2. The method of claim 1 , wherein the specific intent further indicates at least one of conditions and a priority of the specific intent; and/or the one or more targets further indicate at least one of resource limits and a priority of the management subjects.

3. The method of claim 2, wherein at least one of the resource limits and the priority of the management subjects are derived from at least one of the conditions and the priority of the specific intent.

4. The method of claim 2 or 3, wherein the evaluating is further based on at least one of the resource limits and a priority of the one or more targets.

5. The method of any one of claims 1 to 4, wherein the resource pool information describes: a total amount of resources of each of the resource pools which are controlled by the control entities and network functions, and for each resource pool of the resource pools, a per service resource demand for services using resources from the resource pool, and wherein the evaluating is performed for each of the resource pools.

6. The method of any one of claims 1 to 5, wherein the feedback on quality comprises an event sent by a terminating entity of the terminating entities in case it momentarily experiences a degradation of the certain quality.

7. The method of any one of claims 1 to 6, further comprising: maintaining a mapping of each of the end user services to one or more of the resource pools based on the resource pool information.

8. The method of claim 7, further comprising: deciding that the one or more targets are not achievable in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is lower than a sum of a per service resource demand for services using resources from the resource pool; and indicating, to the intent management entity, an enforcement conflict due to capacity of the resource pool.

9. The method of claim 7 or 8, further comprising: in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is not lower than a sum of a per service resource demand for services using resources from the resource pool, reconfiguring the control entities and network functions to control split of the resource pool among the services and align a per service resource allocation with the per service resource demand.

10. The method of claim 9, further comprising: in case the per service resource allocation cannot be aligned with the per service resource demand, deciding that the one or more targets are not achievable; and indicating, to the intent management entity, an enforcement conflict due to allocation granularity.

11 . The method of any one of claims 1 to 10, wherein at least one of the following applies: the intent management entity comprises a non-real time radio intelligent controller, the quality management entity comprises a near-real time radio intelligent controller, the specific intents comprise quality of experience intents, the specific intents are targeting at least one of groups of users, application types, subsets of services or services, the certain subject comprises at least one of a group of users, an application type, a subset of a service or a service, the one or more targets comprise at least one of a target for a specific user, a target for a specific application, a target for a specific subset of a service or a target for a specific service, the management subjects comprise at least one of a specific user, a specific application, a specific subset of a service or a specific service, the terminating entities comprise at least one of a user equipment, an application function and an application server, the one or more targets are provided to the quality management entity as A1 policies through A1 interface, the certain quality comprises a satisfactory quality of experience of the certain subject.

12. The method of any one of claims 1 to 11 , wherein the feedback on quality includes an identifier of the terminating entities.

13. The method of any one of claims 1 to 12, wherein the feedback on quality from the terminating entities is collected via the control entities and network functions.

14. A non-transitory computer-readable storage medium storing a program that, when executed by a computer, causes the computer at least to perform : for each specific intent of a plurality of specific intents received by an intent management entity of an intent-based network, calculating one or more targets to be managed by a quality management entity of the intent- based network, wherein the specific intent indicates that a certain subject has to have a certain quality, wherein the certain subject is associated with an end user service, and wherein the one or more targets indicate management subjects associated with the certain subject and with the end user service; collecting resource pool information from control entities and network functions which control resource pools comprising resources allocated to end user services, wherein the management subjects of the plurality of specific intents are associated with the end user services; collecting feedback on quality from terminating entities terminating the end user services; and evaluating, based on at least one of the resource pool information and the feedback on quality, whether or not the one or more targets of the plurality of specific intents are achievable.

15. An apparatus for use by an intent-based network, the apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to: for each specific intent of a plurality of specific intents received by an intent management entity of the intent-based network, calculate one or more targets to be managed by a quality management entity of the intent- based network, wherein the specific intent indicates that a certain subject has to have a certain quality, wherein the certain subject is associated with an end user service, and wherein the one or more targets indicate management subjects associated with the certain subject and with the end user service; collect resource pool information from control entities and network functions which control resource pools comprising resources allocated to end user services, wherein the management subjects of the plurality of specific intents are associated with the end user services; collect feedback on quality from terminating entities terminating the end user services; and evaluate, based on at least one of the resource pool information and the feedback on quality, whether or not the one or more targets of the plurality of specific intents are achievable.

16. The apparatus of claim 15, wherein the specific intent further indicates at least one of conditions and a priority of the specific intent; and/or the one or more targets further indicate at least one of resource limits and a priority of the management subjects.

17. The apparatus of claim 16, wherein at least one of the resource limits and the priority of the management subjects are derived from at least one of the conditions and the priority of the specific intent.

18. The apparatus of claim 16 or 17, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus further to: evaluate, further based on at least one of the resource limits and a priority of the one or more targets, whether or not the one or more targets of the plurality of specific intents are achievable.

19. The apparatus of any one of claims 15 to 18, wherein the resource pool information describes: a total amount of resources of each of the resource pools which are controlled by the control entities and network functions, and for each resource pool of the resource pools, a per service resource demand for services using resources from the resource pool, and wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus further to: evaluate, for each of the resource pools, whether or not the one or more targets of the plurality of specific intents are achievable.

20. The apparatus of any one of claims 15 to 19, wherein the feedback on quality comprises an event sent by a terminating entity of the terminating entities in case it momentarily experiences a degradation of the certain quality.

21. The apparatus of any one of claims 15 to 20, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus further to: maintain a mapping of each of the end user services to one or more of the resource pools based on the resource pool information.

22. The apparatus of claim 21 , wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus further to: decide that the one or more targets are not achievable in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is lower than a sum of a per service resource demand for services using resources from the resource pool; and indicate, to the intent management entity, an enforcement conflict due to capacity of the resource pool.

23. The apparatus of claim 21 or 22, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus further to: in case there is feedback on quality for an end user service of the end user services, the feedback on quality indicating a degradation of the certain quality, and a total amount of resources of a resource pool of the one or more resource pools to which the end user service is mapped is not lower than a sum of a per service resource demand for services using resources from the resource pool, reconfigure the control entities and network functions to control split of the resource pool among the services and align a per service resource allocation with the per service resource demand.

24. The apparatus of claim 23, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus further to: in case the per service resource allocation cannot be aligned with the per service resource demand, decide that the one or more targets are not achievable; and indicate, to the intent management entity, an enforcement conflict due to allocation granularity.

25. The apparatus of any one of claims 15 to 24, wherein at least one of the following applies: the intent management entity comprises a non-real time radio intelligent controller, the quality management entity comprises a near-real time radio intelligent controller, the specific intents comprise quality of experience intents, the specific intents are targeting at least one of groups of users, application types, subsets of services or services, the certain subject comprises at least one of a group of users, an application type, a subset of a service or a service, the one or more targets comprise at least one of a target for a specific user, a target for a specific application, a target for a specific subset of a service or a target for a specific service, the management subjects comprise at least one of a specific user, a specific application, a specific subset of a service or a specific service, the terminating entities comprise at least one of a user equipment, an application function and an application server, the one or more targets are provided to the quality management entity as A1 policies through A1 interface, the certain quality comprises a satisfactory quality of experience of the certain subject.

26. The apparatus of any one of claims 15 to 25, wherein the feedback on quality includes an identifier of the terminating entities.

27. The apparatus of any one of claims 15 to 26, wherein the feedback on quality from the terminating entities is collected via the control entities and network functions.